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长春光学精密机械与物... [1]
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Non-stationary vibration signal analysis and fault diagnosis method of aircraft power plant using wavelet network
会议论文
Chinese Control and Decision Conference 2008, CCDC 2008, Yantai, Shandong, China, July 2, 2008 - July 4, 2008
作者:
Zhao, Jianming
;
Liu, Jinjun
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浏览/下载:4/0
  |  
提交时间:2017/01/17
Electric fault currents
Aircraft
Curve fitting
Electric power plants
Least squares approximations
Power plants
Signal analysis
Signal processing
Speech recognition
Systems engineering
Telecommunication
Wavelet transforms
Aero engines
Aeroengine
Eigenvectors
Fault diagnosis
Fault diagnosis method
Fault patterns
Feature vectors
Multi-resolution analysis
Network performances
Network structures
Non-stationary
Pattern recognition
Recursive orthogonal least squares algorithm
Self-organizing learning
Self-organizing learning array
Simulation results
Trained network
Training and testing
Vibration signal analysis
Wavelet networks
Wavelet transform
Wavelet packet and neural network basis medical image compression (EI CONFERENCE)
会议论文
4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China
Zhao X.
;
Wei J.
;
Zhai L.
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浏览/下载:14/0
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提交时间:2013/03/25
It is difficult to get high compression ratio and good reconstructed image by conventional methods
we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image
use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network algorithm
not only for its vector quantization feature
but also for its topological property. This property allows an increase of about 80% for the compression rate. Compared to the JPEG standard
this compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30. This method can get big compression ratio and perfect PSNR. Results show that the image can be compressed greatly and the original image can be recovered well. In addition
the approach can be realized easily by hardware.
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